Data Science: The evolution of the Internet of Things

The Internet of Things (IoT) has been hailed as one of the most compelling data science projects of the moment, but what is it, how has it evolved and what does the future hold? Professor Antonio Liotta, Director of the Data Science Research Centre at the University of Derby, discusses the data science possibilities of IoT.

You could describe IoT as the ‘next’ Internet. It broadens the reach of connectivity beyond computers and phones to virtually any piece of technology that has a radio interface and a chip. It gathers data from the electronic sensors found in items such as cars, drones and wearable devices like fitness gadgets.

Beyond sensing and collecting data, IoT can affect the physical world by sending signals to control actuators and robots. This makes it possible to coordinate multiple systems that work together, for example, a traffic and energy management system in a ‘smart’ city. IoT virtualises the physical world, enabling a cyber-physical connection.

The changes to IoT

In 2014, IoT was mainly about the enabling devices and connectivity. Today, IoT is a distributed data science problem.

The general vision of how IoT could potentially transform processes hasn’t changed, but the technologies behind it have progressed considerably. The advances in technology mean we can now connect things more easily, gather data from most physical processes, and collect information from sources that are not necessarily related.

IoT systems are already successfully being used in small-scale systems such as factory automation, autonomous driving, smart homes, and e-health. This type of business model operates through cloud-assisted IoT, where a device captures data then transfers it to a cloud service.

The threat of IoT

We live in a data-hungry age where people are constantly questioning the level of control they have over how their personal data is shared. As the IoT increases connectivity, the ubiquitous sensing and remote actuation also increases which could expose sensitive personal information.

The rate of growth and the risks that it presents is another area of concern for engineers and computer scientists. It is estimated that the internet will grow by three orders of magnitude within a few years. Based on the current technology, there is simply not enough wireless spectrum, energy or data storage to cope with connecting the amount of things this will entail. Before the IoT can reach full potential, there needs to be major scientific breakthroughs in low-power communications and distributed machine learning.

The future of IoT

Despite the challenges, there are exciting times ahead. IoT enables the digitalisation of everything, from tracking your personal sleep habits to monitoring the most complex factory assembly lines. By connecting more things and correlating more data, IoT creates new opportunities to use data analytics and artificial intelligence (AI) to inform businesses across a variety of sectors. IoT has the potential to transform businesses and society. Some of the prospects for utilising this type of process optimisation are energy saving, pollution reduction, and better health.

IoT is a concept (everything connected) and an enabler (an enhanced cyber-physical Internet). With more data available to AI systems, IoT will expand the scope and power of AI. It will also allow computers to remotely control the physical world in ways that we can’t yet imagine.

From an academic perspective, research in data science will continue to grow in interest and importance. But at a societal and technological level, we will have to address ethical questions, not only about privacy, but also about how much authority and autonomy we wish to hand over to the intelligent IoT.